We are looking for a talented and highly motivated Senior Data Analyst to join our Business Intelligence & Insights team and play a key role in shaping the data foundation that powers Kpler's commercial and strategic decision-making. Reporting to the Head of BI, you will own critical data pipelines, architect scalable Looker solutions, and act as a trusted data partner to stakeholders across the business.
This is a high-impact role for someone who thrives at the intersection of data engineering and business analytics, someone who can build robust, production-grade infrastructure one day and translate complex datasets into actionable insights for a commercial audience the next. If you're excited about working with real-time commodity flow data and helping shape the BI strategy of a fast-growing B2B SaaS company, this role is for you.
Key Responsibilities
Architect and maintain scalable LookML models, Explores, and dashboards that serve as the single source of truth for business metrics across commercial, product, and finance teams.
Define and enforce best practices for Looker development including naming conventions, field definitions, derived tables, and data testing to ensure reliability and consistency.
Own the end-to-end delivery of BI reporting features: from requirement gathering to data modelling to dashboard publication.
Continuously optimise LookML for performance, leveraging BigQuery capabilities such as partitioning, clustering, and materialisation strategies.
AI Curiosity & ExperimentationIs genuinely curious about AI tools and how they're evolving
Proactively identifies opportunities to automate repetitive data tasks — whether that's query generation, documentation, or pipeline monitoring
Uses AI to increase their own productivity and brings that mindset to the team
Data Pipeline OwnershipDesign, build, and maintain robust ELT pipelines in BigQuery that ingest, transform, and serve data from internal systems (CRM, ERP, product telemetry) and external APIs.
Take ownership of pipeline reliability implement monitoring, alerting, and data quality checks to proactively identify and resolve issues before they reach stakeholders.
Apply software engineering best practices to the BI codebase: version control via GitHub, peer code reviews, and thorough documentation.
Identify technical debt and propose scalable, maintainable alternatives — always balancing speed of delivery with long-term data platform health.
Stakeholder-Facing AnalyticsPartner directly with commercial, product, and finance stakeholders to translate ambiguous business questions into well-defined data requirements and analytical deliverables.
Act as a trusted data advisor: proactively surface insights, flag data inconsistencies, and guide stakeholders in interpreting metrics correctly.
Communicate complex technical concepts clearly and concisely to non-technical audiences, both in written documentation and live discussions.
Contribute to data literacy across the organisation by promoting self-serve analytics and training stakeholders on Looker capabilities.
Cross-Functional Collaboration & StandardsWork closely with Data Engineering and Product teams to ensure BI needs are considered in upstream data architecture decisions.
Contribute to team rituals — sprint planning, code reviews, design discussions — and help mentor junior team members.
Support team OKRs and KPIs, and take accountability for the quality and accuracy of the analytical assets you own.
We're a team that actively explores how AI can make analytical work faster and sharper. For this role, we're looking for someone who:
Requirements
5 years of experience in analytics, BI development, or a closely related data role.
Solid understanding of data modelling principles: dimensional modelling, slowly changing dimensions, and denormalisation trade-offs.
Experience working in a B2B SaaS environment, ideally with exposure to CRM data (Salesforce), product telemetry, or subscription billing datasets.
Expert-level SQL skills with hands-on experience in BigQuery (or equivalent cloud data warehouse such as Snowflake or Redshift).
Proven experience developing and maintaining production-grade Looker/LookML solutions - you know the difference between a good Explore and a great one.
Comfortable with version control workflows (GitHub/GitLab) and treating the BI codebase as production software.
We're a team that actively experiments with AI to move faster and think sharper — if you're curious about how AI tools can augment analytical work, you'll feel right at home.
Python scripting experience for data wrangling or pipeline automation is advantageous.
Familiarity with dbt or similar transformation tools is a strong plus.
Business-first thinker: you don’t just build what’s asked, you ask why it’s needed and whether there’s a better way to answer the underlying question.
Detail-oriented and rigorous — you have a zero-tolerance mindset for data quality issues and know how to build systems that catch problems early.
Strong communicator who can translate analytical complexity into clear, actionable insights for commercial and executive stakeholders.
Self-directed and comfortable operating in an async, remote-first environment with stakeholders across multiple time zones.
A collaborative team player who gives and receives feedback constructively, and actively contributes to a culture of learning and continuous improvement.
- A degree in Computer Science, Statistics, Mathematics, Business, or a related field.
